Professor Cecilia Lindgren
Watch Cecilia's inaugural lecture "Time Flies: Spending two decades dissecting the aetiology of common complex metabolic traits" on BDI TV.
Director, Big Data Institute
- Professor of Genomic Endocrinology & Metabolism, Nuffield Department of Population Health
- Research Fellow, St Anne's College
Obesity and its consequences are major and growing challenges for health care worldwide. Recently, the first common variants have been identified which influence overall levels of adiposity and predispose to obesity at the population level: these findings should lead to improved understanding of the mechanisms involved in the regulation of overall energy balance. However, not all obese individuals are equally vulnerable to diabetes, insulin resistance and the other adverse consequences of obesity, and it has long been appreciated that the distribution of fat (particularly the degree of central or visceral obesity) is an additional and independent determinant of individual risk of metabolic and cardiovascular disease.
Our research seeks to advance understanding of the mechanisms involved in obesity and the regulation of differential central fat accumulation in the belief that an appreciation of these mechanisms will complement advances in understanding of overall energy balance.
By applying a range of genetic and genomic approaches, we expect to identify genetic variants influencing regional fat distribution, and to illuminate some of the biological pathways involved. Our specific objectives are:
- To undertake identification of genetic variants influencing obesity and individual patterns of fat distribution and central obesity through large-scale genome-wide association meta-analysis and fine-mapping;
- To examine the relationships between sequence variation, expression of mRNA, microRNAs and molecular and physiological phenotypes, in human adipose samples, to identify adipose-specific pathways relevant to individual differences in obesity and central fat distribution;
- To follow-up of the key findings from genetic, epidemiological and functional perspectives.
This knowledge should support translational advances in the management of obesity through development of novel diagnostic and therapeutic options
Genic constraint against nonsynonymous variation across the mouse genome.
Powell G. et al, (2023), BMC Genomics, 24
Discovering cellular programs of intrinsic and extrinsic drivers of metabolic traits using LipocyteProfiler.
Laber S. et al, (2023), Cell Genom, 3
Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank
Lassen FH. et al, (2023)
Genome-wide association study and functional characterization identifies candidate genes for insulin-stimulated glucose uptake.
Williamson A. et al, (2023), Nat Genet, 55, 973 - 983
A non-coding variant linked to metabolic obesity with normal weight affects actin remodelling in subcutaneous adipocytes.
Glunk V. et al, (2023), Nat Metab, 5, 861 - 879